Method and apparatus for retrieving a video and audio scene using an index generated by speech recognition

ABSTRACT

A video retrieval apparatus includes a retrieval data generator that is configured to extract a characteristic pattern from a voice signal synchronous with a video signal to generate an index for video retrieval. The video retrieval apparatus also includes a retrieval processor that is configured to input a key word from a retriever and collate the key word with the index to retrieve a desired video. The retrieval data generator includes a multiplexor that is configured to multiplex video signals, voice signals and indexes to output in data stream format. The retrieval processor includes a demultiplexor that is configured to demultiplex the multiplexed data stream into the video signals, the voice signals and the indexes. A video reproduction apparatus may collate a visual pattern of the key word visual pattern data of the video signal at the time a person vocalizes a sound as the index for retrieval.

TECHNICAL FIELD

The present invention relates to a video retrieval apparatus and methodcapable of retrieving a desired scene (video and/or voice) using a keyword.

BACKGROUND ART

Recently rapidly popularized computer networks represented bymulti-channel broadcast and the internet distribute a huge amount ofvideos to societies including homes. Meanwhile increased recordingmedium capacity enables a large amount of video signals to be stored inthe homes. This phenomenon requires techniques for retrieving a videoscene that a user desires from the large number of video signals easilyand with high accuracy.

Conventionally considered methods are a method that detects a changingpoint of video signals from a variation of the video signals to displaya video scene according to the point, and retrieval systems such as amethod that detects a particular scene comprised of particular objectsto display using an image recognition technique. However there is aproblem that in these retrieval systems, a user's purpose of retrievingis not always reflected on a retrieved scene accurately.

Further there is a retrieval system that reads subtitle information andclosed caption information that American broadcast adopts from videos bycharacter recognition to retrieve a particular scene. This systemenables a user to acquire the scene on which the user's purpose ofretrieving is reflected accurately in scenes well-adopting the subtitleinformation and closed caption. However, since such information islimited to part of broadcast programs because the information needs tobe inserted manually, it is difficult to widely apply the information togeneral videos.

On the other hand, it is expected that using as a key word voiceinformation accompanying videos achieves a retrieval system thatreflects a retrieval purpose accurately. Unexamined Japanese PatentPublication HEI6-68168 discloses a video retrieval system that retrievesa desired scene using a voice key word.

FIG. 1 illustrates a functional block diagram of the retrieval systemdisclosed in above-mentioned Unexamined Japanese Patent PublicationHEI6-68168. Voice/video input section 201 receives a voice signal andvideo signal, voice signal storage section 202 stores the received voicesignal, and video signal storage section 203 stores the received videosignal. Voice analysis section 204 analyzes the voice signal to generatesequence of characteristic parameters representative of characteristicsof the voice. Voice characteristic storage section 205 stores thegenerated sequence of characteristic parameters.

Meanwhile a key word for a user to use in a scene retrieval later isprovided in the form of a voice to key word characteristic analysissection 206. Key word characteristic analysis section 206 analyzes thevoice as the key word to generate sequence of characteristic parametersrepresentative of characteristics of the key word. Key wordcharacteristic parameter storage section 207 stores the generatedsequence of characteristic parameters.

Key word interval extraction section 208 compares the sequence ofcharacteristic parameters of the voice signal stored in the storagesection 202 with the sequence of characteristic parameters of the keyword voice, and extracts a key word interval in the voice signal. Indexaddition section 209 generates index position data 210 that relates theextracted key word interval to a frame number of the video signalcorresponding to the voice signal.

When a retrieval is performed using index position data 210, it ispossible to designate the frame number of the video signal in which thekey word appears using the voice signal, thereby enabling video/voiceoutput section 211 to output a corresponding video and voice, andconsequently to present the user desired video and voice.

However there is a problem that it is necessary to register in advance avoice key word to be used in a retrieval, and that it is not possible toretrieve using other key words. In particular, a user input uncertainkey word results in a retrieval error, and thereby it is not possible toretrieve a scene reflecting a retrieval purpose accurately.

DISCLOSURE OF INVENTION

The present invention is carried out in view of foregoing. It is anobject of the present invention to provide an apparatus and methodcapable of retrieving a scene that a user desires in retrieving a videoand/or voice, using an out-of-vocabulary word other than words and keywords that are registered in advance for example, in a dictionary, andan uncertain key word that the user inputs.

The present invention provides a scene retrieval system which applies aseries of voice recognition processing procedures separately togeneration of retrieval data and retrieval processing, and thereby whichis capable of retrieving a video/voice scene that a user desires withhigh speed, and reproducing the scene with high speed.

Further it is designed to generate sequence of a score of a subword,which is an intermediate result of the voice recognition processing, asa retrieval index in generating retrieval data, and to convert an inputkey word into time series of subword to collate with the retrieval indexin retrieval processing.

Therefor it is not necessary to collate with a word dictionary or aretrieval key word registered in advance, and thereby the problem,so-called out-of-vocabulary word problem, is solved that it is notpossible to cope with an unregistered key word. Further it is possibleto retrieve a video/voice scene with the highest reliability even when auser inputs an uncertain key word.

Moreover the sequence of the score of the subword that is the retrievalindex is multiplexed in a data stream along with the video signal andvoice signal, whereby it is possible to transmit the retrieval indexthrough broadcast networks and communication networks such as theinternet.

The subword is a basic unit of an acoustic model that is smaller than asingle word. Examples of the subword is a phoneme, syllable such asconsonant-vowel and vowel-consonant-vowel, and demisyllable. Each wordis represented as a sequence of subwords.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a functional block diagram of a current video retrievalsystem;

FIG. 2 is a functional block diagram of a scene retrieval systemaccording to a first embodiment of the present invention;

FIG. 3 is a data structure diagram of a standard voice pattern;

FIG. 4 is a diagram illustrating a phoneme similarity table;

FIG. 5 is a diagram illustrating a situation in which subwordscorresponding to a phoneme sequence of a key word are picked up from thephoneme similarity table;

FIG. 6 is a diagram illustrating a situation in which picked-up subwordsare arranged in the order of the phoneme sequence of the key word;

FIG. 7 is a functional block diagram of a scene retrieval systemaccording to a second embodiment of the present invention;

FIG. 8(1) is a structure diagram of an MPEG stream in which videosignals, voice signals and video retrieval indexes are multiplexed;

FIG. 8(2) is a structure diagram of a video stream;

FIG. 8(3) is a structure diagram of GOP;

FIG. 8(4) is a structure diagram of a retrieval data stream;

FIG. 9 is a functional block diagram of a scene retrieval systemaccording to a third embodiment of the present invention;

FIG. 10 is a functional block diagram of a video recording apparatusaccording to a fourth embodiment of the present invention;

FIG. 11 is a functional block diagram of a video recording apparatusaccording to a fifth embodiment of the present invention; and

FIG. 12 is a functional block diagram of a video reproduction apparatusaccording to a sixth embodiment of the present invention.

BEST MODE FOR CARRYING OUT THE INVENTION

Embodiments of the present invention are explained below with referenceto accompanying drawings.

First Embodiment

FIG. 2 is a functional block of a scene retrieval system according tothe first embodiment of the present invention. The scene retrievalsystem of this embodiment has retrieval data generation section 100 thatgenerates a video retrieval index for use in retrieving a desired scenefrom among stored images, and retrieval processing section 200 thatcollates an input retrieval key word with the video retrieval index toretrieve a scene reflecting a retrieval purpose accurately.

Retrieval data generation section 100 has video signal input section 101that receives a video signal, and voice signal input section 102 thatreceives a voice signal accompanying (synchronous with) the videosignal. Storage section 201 provided in retrieval processing section 200stores the video signal and voice signal respectively input from videosignal input section 101 and voice signal input section 102. The voicesignal input from voice signal input section 102 is further input tovoice characteristic pattern extraction section 103. Voicecharacteristic pattern extraction section 103 analyzes the voice signalto extract a voice characteristic pattern. The extracted voicecharacteristic pattern is provided to video retrieval index generationsection 104. Video retrieval index generation section 104 compares theextracted voice characteristic pattern with a standard voice patternstored in standard voice characteristic pattern storage section 105, andoutputs a group of a beginning, ending time and score indicative of asimilarity of a best-matching subword, as a video retrieval index. Thevideo retrieval index is stored in storage section 201 in retrievalprocessing section 200.

Retrieval processing section 200 has storage section 201 that storesvideo signals, voice signals and video retrieval indexes. Storagesection 201 has a phoneme similarity table formed with the videoretrieval indexes. The phoneme similarity table will be described later.Control section 202 controls read positions of the video signals andvoice signals stored in storage section 201. Key word input section 203inputs a retrieval key word for use in retrieving a desired video scenefrom among videos stored in storage section 201. Key word conversionsection 204 converts the input key word into time series of the subwordcomposing the input key word. Key word pattern collation section 205fetches the video retrieval index matching the subword of the input keyword from storage section 201. The section 205 reconstructs theretrieval key word using the video retrieval index fetched from storagesection 201, and calculates a score of each of the reconstructed keywords. Based on a beginning time of a head subword of the reconstructedkey word with a high score, control section 202 retrieves acorresponding video scene from storage section 201. Video signalscomposing the retrieved video scene output from storage section 201 areoutput outside from video signal output section 206, and voice signalsaccompanying the video signals are output outside from voice signaloutput section 207.

The following explains in detail about processing for generating thevideo retrieval index in retrieval data generation section 100. Voicecharacteristic pattern extraction section 103 divides an input voicesignal into analysis frames of 10 msec sequentially, and performs FastFourier transform on each analysis frame to convert into acousticproperty data representative of acoustic properties at a human voicefrequency band. Further the section 103 converts the acoustic propertydata of the voice frequency band into vector data with N (N is anarbitrary natural number) components comprised of acousticcharacteristic amounts. This vector data is used as a voicecharacteristic pattern. As the acoustic characteristic amount, it ispreferable to use short-time spectra or logarithmic value of the spectraat the voice frequency band of an input voice, or logarithmic energy ofthe input voice at a predetermined interval.

Thus, the input voice is converted into the voice characteristic pattern(vector data) for every 10 msec, and the converted voice characteristicpattern is sequentially output to video retrieval index generationsection 104. In addition a frame length of the analysis frame is notlimited to 10 msec.

Standard voice characteristic pattern storage section 105 storessubwords (#V, #CV, #CjV, CV, CjV, VC, QC, VQ, VV, and V#, where C is aconsonant, V is a vowel, j is, Q is a double consonant, and # is silent)in advance as standard voice patterns. Voices collected from a pluralityof speakers are analyzed in advance to extract voice characteristicpatterns per subword basis. The extracted voice characteristic patternsare subjected to statistical processing, and then registered as thestandard voice patterns. Specifically, standard voice characteristicpattern storage section 105 stores a table relating each subword to astandard voice pattern thereof (extracted voice characteristic pattern).FIG. 3 illustrates specific examples of the standard voice patterns.About 500 standard voice patterns are prepared in this figure. Howeverthe number of standard voice patterns to be stored in standard voicecharacteristic pattern storage section 105 is not limited to 500, andmay be determined as appropriate in a relationship between a computationamount and retrieval accuracy.

Video retrieval index generation section 104 fetches a first standardvoice pattern from standard voice characteristic pattern storage section105, and obtains a similarity between the first standard voice patternand a voice characteristic pattern of an input voice using voicerecognition processing. As the voice recognition processing, it ispreferable to use voice recognition methods such as DP collation methodand HMM. The section 104 detects as a subword interval an intervalindicative of the highest similarity with respect to the first standardvoice pattern, and obtains a beginning time, ending time and a score,which is the similarity, of the detected subword interval. With respectto the thus detected subword interval corresponding to the firststandard voice pattern, the group of the beginning time, ending time andscore is output as a single video retrieval index. In other words, thesingle video retrieval index is comprised of a phoneme sign, beginningtime, ending time and score.

After obtaining the video retrieval index corresponding to the firststandard voice pattern, a second standard voice pattern is fetched fromstandard voice characteristic pattern storage section 105. Then thesection 104 compares the voice characteristic pattern of the same voiceinterval as described above with the second standard voice pattern,detects a subword interval with respect to the second standard voicepattern in the same way as described above, and outputs the group ofbeginning time, ending time and score of the detected subword intervalas the video retrieval index. Thereafter, in the same way as describedabove, the section 104 detects respective similarities between the voicecharacteristic pattern of the same voice interval and each of the otherleft standard voice patterns while switching between the standard voicepatterns, and generates video retrieval indexes each comprised of thegroup of the beginning time, ending time and score on all the standardvoice patterns.

After generating the video retrieval indexes of all the standard voicepatterns in a voice interval of the input voice, video retrieval indexgeneration section 104 shifts a voice interval to be processed to a nextvoice interval neighboring to the processed interval to execute the sameprocessing. Thereafter in the same way as described above, the section104 generates retrieval indexes over all the intervals of the inputvoice to complete the processing, while shifting the voice interval tobe processed.

The following explains in detail about processing for retrieving a videoscene using a key word in retrieval processing section 200.

FIG. 4 illustrates part of a lattice structure of video retrievalindexes. An end of each voice interval of 10 msec divided from the inputvoice is set to be an end of each of the video retrieval indexesgenerated in the voice interval, and the video retrieval indexes in thesame voice interval are arranged in the order of generation, whereby thevideo retrieval indexes are arranged in the form of lattices over anentire input voice. Thus obtained lattice structure of the voiceretrieval indexes is referred to as a phoneme similarity table. In thephoneme similarity table, each video retrieval index is representativeof the group of the score and a length corresponding to the beginningtime thereof. FIG. 4 illustrates five kinds of subwords of “A”, “KA”,“SA”, “TA” and “NA” as representative examples among the phonemesimilarity table of video retrieval indexes.

It is assumed that key word input section 203 receives “SORA” as aretrieval key word. Key word conversion section 204 converts “SORA” ofthe retrieval key word into a sequence of subwords. “SORA” is convertedinto “SO, OR, and RA”.

Key word pattern collation section 205 picks up subwords composing theretrieval key word from among the phoneme similarity table. In otherwords, the section 205 only picks up subwords “SO”, “OR”, and “RA”composing the retrieval key word among lattices at each time. FIG. 5illustrates picked up lattices each comprised of one of subwords “SO”,“OR”, and “RA” of the retrieval key word.

Key word pattern collation section 205 connects subwords “SO”, “OR” and“RA” on a plurality of picked up lattices in the order of the sequenceof subwords converted from the retrieval key word with no space insertedbetween the subwords. The section 205 fetches a final subword “RA” of alattice ending at a time, fetches a subword “OR”, before the final one,on another lattice ending at the beginning time of “RA”, further fetchesa subword “SO”, before the “OR”, on the other lattice ending at thebeginning time of “OR”, and connects “SO”, “OR” and “RA” using the endof final subword “RA” as a reference.

With respect to a key word thus reconstructed by connecting “SO”, “OR”and “RA”, key word pattern collation section 205 calculates a score ofthe reconstructed key word. Specifically the section 205 adds scoresassigned for subwords “SO”, “OR” and “RA” composing the reconstructedkey word. This addition value is the score of the reconstructed keyword. Thereafter in the same way as described above, the section 205generates reconstructed key words sequentially at all the times, whileshifting the ending time of the subword “RA”, and calculates the scoreof each reconstructed key word. FIG. 6 illustrates reconstructed keywords obtained by shifting the ending time of the subword “RA”.

Key word pattern collation section 205 processescompression/decompression processing on each constructed key word(sequence of the subword) using, for example, DP collation method, inconsideration of expansion and contraction characteristics of a voice.Then the section 205 calculates scores of all the reconstructed keywords, and outputs these scores of the reconstructed key words tocontrol section 202.

Control section 202 calculates a timecode of a video signalcorresponding to the beginning time of a head subword of thereconstructed key word with a high score, and performs control toreproduce corresponding parts of the video and voice signals stored instorage section 201. As a result, reproduced video and voice signals arerespectively output from video signal output section 206 and voicesignal output section 207.

Thus sequence of a subword assigned a score is generated from a voicesignal accompanying a video signal to be retrieved, and the data isstored as a video retrieval index in storage section 201, while inretrieving, a key word is converted into subwords to collate with videoretrieval indexes. Therefore it is possible to cancel a storage sectionwith a word dictionary and/or retrieval key words registered in advance,and there is another advantage that the out-of-vocabulary word problemis not generated.

Further since the collation with the key words registered in advance isnot performed, it is possible to retrieve the most reliable video sceneeven in the case where a user inputs an uncertain key word, and thus toprovide an excellent effect.

Second Embodiment

A scene retrieval system according to the second embodiment of thepresent invention transmits a video retrieval index generated in aretrieval data generation apparatus to a retrieval apparatus via atransmission medium.

FIG. 7 illustrates a configuration of the scene retrieval systemaccording to the second embodiment. In the figure, the same marks areused for sections with the same functions as the first embodiment asdescribed above. The scene retrieval system is comprised of retrievaldata generation apparatus 120 that multiplexes video retrieval indexesgenerated from a voice signal accompanying a video signal in a datastream, retrieval apparatus 200 that collates a subword of a retrievalkey word with the video retrieval indexes to retrieve a desired videoscene, and transmission medium 230 for use in transmitting the datastream with the video retrieval indexes multiplexed in retrieval datageneration apparatus 120 to retrieval apparatus 220. Transmission medium230 includes, for example, broadcast networks, communication networksand recording media. The broadcast networks include terrestrialbroadcast networks and cable broadcast networks, and the communicationnetworks include the internet. The broadcast networks further includeradio broadcast networks in retrieving a voice scene.

Retrieval data generation apparatus 120 is provided with video signalinput section 101, voice signal input section 102, voice characteristicpattern extraction section 103, video retrieval index generation section104, and standard voice pattern storage section 105. Retrieval datageneration apparatus 120 further has multiplexing section 121 thatmultiplexes video retrieval indexes generated in video retrieval indexgeneration section 104, video signals and voice signals. While it ispreferable for multiplexing section 121 to multiplex the video retrievalindexes, video signals and voice signals in an MPEG stream, it may bepossible to multiplex in other data streams.

Retrieval apparatus 220 is provided with storage section 201, controlsection 202, key word input section 203, key word conversion section204, key word pattern collation section 205, video signal output section206, and voice signal output section 207. Retrieval apparatus 200further has demultiplexing section 221 that demultiplexes the videoretrieval indexes, video signals and voice signals from the data streamin which the video retrieval indexes, video signals and voice signalsare multiplexed.

Video retrieval index generation section 104 provided in retrieval datageneration apparatus 120 generates the video retrieval indexes from aninput signal in the same way as in the first embodiment as describedabove. The generated video retrieval indexes are output to multiplexingsection 121. In addition, the video signal received in video signalinput section 101 and the voice signal received in voice signal inputsection 102 are output to multiplexing section 121.

Multiplexing section 121 converts the video signals, voice signals, andvideo retrieval indexes respectively into a plurality of video streams(video stream (1) to video stream (n)), voice streams (voice stream (1)to voice stream (n)), and private streams to store user data (thesestreams are used in transmitting video retrieval indexes, and referredto as retrieval data streams: retrieval data stream (1) to retrievaldata stream (n)).

FIG. 8(1) illustrates a frame structure of the MPEG stream in which thevideo retrieval indexes, video signals and voice signals aremultiplexed. Stream head 101 is to added to a head of the MPEG stream toidentify the stream. FIG. 8(2) illustrates a structure of the videostream. The video stream is comprised of a plurality of GOP (Group ofVideos: GOP(1) to GOP(n)). FIG. 8(3) illustrates a structure of the GOP.The GOP is comprised of a series of groups of an intra-frame coded Ivideo (I(1)), P videos (P(2) to P(m)) coded by motion compensationprediction with reference to the I video or P video, an I videopositioned timewise before and after, and B videos (B−1) to B(m−1))coded by the motion compensation prediction from both videos withreference to P videos. FIG. 8(4) illustrates a structure of the dataretrieval stream. The video retrieval indexes (video retrieval index (1)to video retrieval index (n)) are arranged as units corresponding to aseries of video frames.

The MPEG stream multiplexed in multiplexing section 121 is transmittedto retrieval apparatus 220 through transmission media 230 to be storedin storage section 201. In retrieval apparatus 220, demultiplexingsection 221 demultiplexes the retrieval indexes from the multiplexedMPEG stream to provide to key word pattern collation section 205. A keyword is collated with the video retrieval indexes, and reconstructed keywords are generated in the same way as the first embodiment. Controlsection 202 accesses to the GOP corresponding to a beginning time of thereconstructed key word with a high score to retrieve a video scene. Inaddition it may be possible to demultiplex the video signals and voicesignals along with the video retrieval indexes when the indexes aredemultiplexed from the MPEG stream, to store in storage section 201.

Thus, since the video retrieval indexes per subword basis of the inputvoice are multiplexed in the data stream along with the video signalsand voice signals, it is possible to provide the video retrieval indexesto a user along with videos using the broadcast networks andcommunication networks.

In addition the GOP is unit video reproduction in the MPEG. Thereforewhen the unit retrieval index is brought into coincidence with the GOP,it is possible to start reproducing a desired video scene with ease byaccessing to the GOP corresponding to the retrieval index correspondingto an input key word at the time of retrieval processing.

Third Embodiment

The third embodiment describes a scene retrieval system in which when aretrieval key word is input from a user terminal, a server systemconnected to the user terminal through communication networks provides acorresponding scene.

FIG. 9 illustrates a system configuration of the scene retrieval systemaccording to the third embodiment. In FIG. 9, the same marks are usedfor sections with the same functions as the first embodiment and secondembodiment as described above. The server system is comprised ofretrieval data generation section 100 and retrieval processing section230, and retrieves a video scene that a user desires to transmit to theuser terminal.

Retrieval data generation section 100 is comprised of video signal inputsection 101, voice signal input section 102, voice characteristicpattern extraction section 103 and video retrieval index generationsection 104.

Retrieval processing section 230 is provided with storage section 201,control section 202, and key word pattern collation section 205. Furtherretrieval processing section 230 has key word reception section 231 thatreceives data of a retrieval key word transmitted from user terminal 300through transmission medium 230, and multiplexing section 232 thatmultiplexes a video signal and voice signal of a retrieved scene in adata stream to transmit to user terminal 300 through transmission medium230.

User terminal 300 is provided with key word input section 203, key wordconversion section 204, video signal output section 207 that outputs thevideo signal of the retrieved scene, and voice signal output section 206that outputs the voice signal of the retrieved scene. User terminal 300further has key word transmission section 301 that transmits subwords ofthe retrieval key word converted in key word conversion section 204 toretrieval processing section 230 through transmission medium 230, anddemultiplexing section 302 that demultiplexes the video signal and voicesignal from the data streams received from retrieval processing section203 through transmission medium 230.

In the scene retrieval system configured as described above, userterminal 300 inputs the retrieval key word. In user terminal 300, keyword conversion section 204 converts the input key word into subwords ofthe input key word. Then key word transmission section 301 transmits thesubwords of the input key word through transmission medium 230.Communication networks such as the internet are preferable astransmission medium 230 in this embodiment.

Storage section 201 in retrieval processing section 230 stores, in thesame way as the first embodiment as described previously, video signals,voice signals and video retrieval indexes with a lattice structure. Keyword reception section 231 provides received key word data to key wordpattern collation section 205. Key word pattern collation section 205picks up, as described as previously, video retrieval indexes each witha phoneme sign matching one of the subwords of the key word among thelattice structure of the video retrieval indexes, and generates areconstructed key word at each time. Then control section 202 retrievescorresponding video signals and voice signals based on a beginning timeof the reconstructed key word with a high score. The video signals andvoice signals of the thus retrieved scene are multiplexed in the datastream in multiplexing section 232, and transmitted to user terminal 300through transmission medium 230.

In user terminal 300, demultiplexing section 302 demultiplexes the videosignals and voice signals from the data stream transmitted correspondingto the retrieval key word. The demultiplexed video signals and voicesignals are respectively output from video signal output section 206 andvoice signal output section 207.

Thus connecting user terminal 300 and the server system (retrieval datageneration section 100 and retrieval processing section 230) throughcommunication network 230 enables user terminal 300 that does not havefunctions for generating and retrieving the video retrieval indexes toretrieve a desired scene.

In addition, while in the aforementioned third embodiment, user terminal300 is provided with key word conversion section 204, it may be possibleto provide retrieval processing section 230 with key word conversionsection 204. According this configuration, it is possible to perform theabove-mentioned retrieval without installing new software in a currentuser terminal.

Fourth Embodiment

The fourth embodiment describes an example that the scene retrievalsystem of the present invention is applied to a video recordingapparatus. The video recording apparatus according to this embodimentdetects a human voice from voice signals obtained in video recording,and extracts acoustic property data obtained from the voice as voicecharacteristic pattern data. Further the apparatus forms the voicecharacteristic pattern data into a time information added indexstructure to record in a recording medium along with a video signal andvoice signal.

FIG. 10 illustrates a configuration of the video recording apparatusaccording to this embodiment. Control signal input section 1 receivessignals such as a video recording instruction control signal input froman external. Video recording control section 2 issues a recording startinstruction signal and halt instruction signal to each block composingthe apparatus corresponding to types of received control signals.

Meanwhile, voice signal input section 3 converts analog voice signalsinput after the video recording is started into digital voice signals,and voice signal encoding section 4 performs compression processing suchas the MPEG on the digital voice signals. Video signal input section 5converts analog video signals input after the video recording is startedinto digital video signals, and video signal encoding section 6 performscompression processing such as the MPEG on the digital video signals.

Voice signal input section 3 inputs the digital voice signals to voicecharacteristic pattern extraction section 10. Voice characteristicpattern extraction section 10 detects the acoustic property data of thehuman voice from the input digital voice signals to acquire the voicecharacteristic pattern data. Video retrieval index generation section 11makes the voice characteristic pattern data provided from voicecharacteristic pattern extraction section 10 into packets at timeintervals synchronous with video signals to form into the videoretrieval index structure with the time information added thereto.

Complex data storage processing section 7, instructed from videorecording control section 2, multiplexes the compressed video signalsand voice signals, and the video retrieval indexes to store in videostorage medium 9 such as DVD in recording format. Video storage medium 9is comprised of, for example, an optical disk, HDD (magnetic disk),memory card or magnetic tape. Storage medium operation control section 8performs physical control such as a seek to a recording position invideo storage medium 9, by a control instruction from complex datastorage processing section 7. The video recording apparatus configuredas described above may be comprised of, for example, a microcomputerincorporated device or dedicated LST circuits. In this video recordingapparatus, a voice characteristic pattern extraction step is comprisedof voice characteristic pattern extraction section 10, and an indexinformation storage step is comprised of video retrieval indexgeneration section 11 and complex data storage processing section 7.

The following explains about the operation of this apparatus.

When control signal input section 1 receives a control signalinstructing video recording from an external input device such a remotecontrol device or keyboard, the section 1 converts the control signalinto a signal of format adapted to the apparatus, and issues the videorecording instruction signal to video recording control section 2. Videorecording control section 2 receives the video recording instructionsignal, and instructs each section composing the apparatus to startvideo recording to shift an apparatus state to a video recording state.

Voice signal input section 3 receives the instruction for starting thevideo recording, performs A/D conversion on voice signals input from anexternal device such as a television signal tuning device, microphone,or VTR to quantize, and provides the voice signals to voice signalencoding section 4 and voice characteristic pattern extraction section10 sequentially. Voice signal encoding section 4 performs voice signalband compression processing such as the MPEG on the provided voicesignals to output to complex data storage processing section 7sequentially.

Voice characteristic pattern extraction section 10 receives the voicesignals provided from voice signal input section 3, performs FFT (FastFourier Transform) on the voice signals per unit time, extracts theacoustic property data at a human voice frequency band, and generatesthe voice characteristic pattern data that is vector data with N (N isan arbitrary natural number) components comprised of acousticcharacteristic amounts generally used in voice recognition processing,such as short-term spectral data or logarithmic value of spectra at theextracted frequency band, and logarithmic energy of the voice signalsper unit time.

Voice characteristic pattern extraction section 10 sequentially outputsthe extracted and generated voice characteristic pattern data to videoretrieval index generation section 11. Video retrieval index generationsection 11 collects items of the voice characteristic pattern data,input sequentially, per unit time enabling synchronization between thevideo signals and voice signals with the time series maintained, to makeinto packets, and adds time information and an identification indicativeof the voice characteristic pattern data to each packet. Thereby anindex structure is generated that enables access to the video signals orvoice signals by referring to the time information using a position ofthe voice characteristic pattern data. The section 11 outputs thegenerated index structure packets to complex data storage processingsection 7 sequentially.

Meanwhile video signal input section 5 also receives the instruction forstarting the video recording, performs A/D conversion on video signalsinput from an external device such as the television signal tuningdevice, camera, or VTR to quantize, and provides the video signals aspredetermined video signals to video signal encoding section 6. Videosignal encoding section 6 performs video signal band compressionprocessing such as the MPEG on the provided digital video signals tooutput to complex data storage processing section 7 sequentially.

Complex data storage processing section 7 receives the instruction forstarting the video recording, issues the control signal to storagemedium operation control section 8 before starting recording data, andholds a data recording starting position in storage medium 9. Complexdata storage processing section 7 receives the video signals and voicesignals each applied the signal band compression processing, and theindex structure packets generated in video retrieval index generationsection 11, multiplexes the video signals, voice signals and indexstructure packets in predetermined format such as the MPEG, issues thecontrol signal to recording storage operation control section 8, andrecords the multiplexed data at a predetermined position on videostorage medium 9 according to the recording format such as the DVD.

The sequence of operations as described above is iterated during thetime from video recording is started to video recording control section2 detects elapse of video recording time, finish of video signal inputfrom the external, video recording halt instruction by the controlsignal from the external, or an error notification from a section insidethe apparatus. When video recording control section 2 detects either ofthe above-mentioned conditions, the section 2 instructs each sectioncomposing the apparatus to halt the video recording, shits the apparatusstate to the initial state, and thereby finishes the operation.

While the above-mentioned index structure packets are comprised of timeseries of the voice characteristic pattern data, it may be possible thatvideo retrieval index generation section 11 performs phoneme recognitionprocessing on the time series of the voice characteristic pattern datato convert the index structure packets into the time series of a phonemesimilarity table that is a result of time series pattern collation foreach subword.

In other words, video retrieval index generation section 11 calculates asimilarity between the time series of the voice characteristic patterndata sequentially input from voice characteristic pattern extractionsection 10, and standard patterns per subword basis stored in advance invideo retrieval index generation section 11, to generate the phonemesimilarity table.

Herein, the standard voice patterns per subword basis are phoneme timeseries such as short-term spectral data in the same way as the voicecharacteristic pattern. A collation interval is fixed to a predeterminedtime also with respect to input voice characteristic pattern data, andthe section 11 performs time series pattern collation on the phonemetime series of the standard voice pattern and that of the voicecharacteristic pattern data using, for example, DP (Dynamic Programming)collation method.

In the time series pattern collation, the collation interval is obtainedin the time series of the voice characteristic pattern data that is themost similar to the standard voice pattern per subword basis, and thecollation results are summarized as the phoneme similarity table. Inaddition, the phoneme similarity table is comprised of columns of anidentification (phoneme sign) of each subword, a voice interval(beginning time and ending time) that is the collation interval that isthe most similar to a corresponding subword, and the similarity, and ofrows corresponding to the number of subwords stored as standard voicepatterns.

The section 11 fetches M (M is an arbitrary natural number) items indescending of similarity from the generated phoneme similarity table toreconstruct the similarity table, and collects the similarity tables perunit time enabling synchronization between the video signals and voicesignals with the time series maintained to make into packets. Thesection further adds time information and an identification indicativeof the phoneme similarity table data to each packet, thereby generatesan index structure packet enabling access to the video signals and voicesignals by referring to the time information using a position of phonemesimilarity table data, and outputs the generated packet to complex datastorage processing section 7 sequentially.

The thus generated index structure packet comprised of the time seriesof phoneme similarity table data is stored in video storage medium 9 asa video retrieval index in recording format through complex date storageprocessing section 7.

Thus, the retrieval indexes comprised of the time series of the phonemesimilarity table are generated from voice signals in video recording,and the complex data storage processing section 7 multiplexes theindexes, video signals, and voice signals to store in video storagemedium 9. Therefore it is possible to access to a desired video signaland voice signal with ease using the video retrieval index later. Theretrieval indexes generated in this embodiment have the same structureas the video retrieval indexes in the first embodiment, and therefore itmay be possible to perform key word retrieval in the same way as in thefirst embodiment.

Fifth Embodiment

A video recording apparatus according to the fifth embodiment extractsvisual characteristic pattern data from video signals indicative ofhuman vocalizing, and stores the visual characteristic pattern data asthe video retrieval index.

FIG. 11 illustrates a configuration of the video recording apparatusaccording to this embodiment. Control signal input section 1 receivessignals such as video recording instruction control signal input from anexternal. Video recording control section 2 issues recording startinstruction signal and halt instruction signal to each block composingthe apparatus corresponding to types of received control signals.

Meanwhile, voice signal input section 3 converts analog voice signalsinput after the video recording is started into digital voice signals,and voice signal encoding section 4 performs compression processing suchas the MPEG on the digital voice signals. Video signal input section 5converts analog video signals input after the video recording is startedinto digital video signals, and video signal encoding section 6 performscompression processing such as the MPEG on the digital video signals.

Voice signal input section 3 inputs the digital voice signals to voicecharacteristic pattern extraction section 10. Voice characteristicpattern extraction section 10 detects acoustic property data of a humanvoice from the input digital voice signals to acquire voicecharacteristic pattern data. Further video signal input section 5provides the digital voice signals to visual characteristic patternextraction section 12. Visual characteristic pattern extraction section12 detects an image of a human lip area from input video signals toextract visual characteristic pattern data. Video retrieval indexgeneration section 11 makes each of the voice characteristic patterndata provided from voice characteristic pattern extraction section 10and the visual characteristic pattern data provided from visualcharacteristic pattern extraction section 12 into packets at timeintervals synchronized with video signals, to form into the videoretrieval index structure with time information and pattern dataidentification added thereto.

Complex data storage processing section 7, instructed from videorecording control section 2, multiplexes the compressed video signalsand voice signals, and the video retrieval indexes to store in videostorage medium 9 such as a DVD in recording format. Video storage medium9 is comprised of, for example, an optical disk, HDD (magnetic disk),memory card or magnetic tape. Storage medium operation control section 8performs physical control such as a seek to a recording position invideo storage medium 9, by a control instruction from complex datastorage processing section 7. The video recording apparatus configuredas described above may be comprised of, for example, a microcomputerincorporated device or dedicated LST circuits.

The following explains about the operation of this apparatus.

When control signal input section 1 receives a control signalinstructing video recording from an external input device such as aremote control device or keyboard, the section 1 converts the controlsignal into a signal of format adapted to the apparatus, and issues thevideo recording instruction signal to video recording control section 2.Video recording control section 2 receives the video recordinginstruction signal, and instructs each section composing the apparatusto start video recording to shift an apparatus state to a videorecording state.

Voice signal input section 3 receives the instruction for starting thevideo recording, performs A/D conversion on voice signals input from anexternal device such as a television signal tuning device, microphone,or VTR to quantize, and provides the voice signals to voice signalencoding section 4 and voice characteristic pattern extraction section10 sequentially. Voice signal encoding section 4 performs voice signalband compression processing such as the MPEG on the provided voicesignals to output to complex data storage processing section 7sequentially.

Voice characteristic pattern extraction section 10 receives the voicesignals provided from voice signal input section 3, performs FFT (FastFourier Transform) on the voice signals per unit time, extracts theacoustic property data at a human voice frequency band, and generatesvector data with N (N is an arbitrary natural number) componentscomprised of acoustic characteristic amounts generally used in voicerecognition processing, such as short-term spectral data or logarithmicvalue of spectra at the extracted frequency band, and logarithmic energyof the voice signals per unit time, which is used voice characteristicpattern data in the present invention.

Voice characteristic pattern extraction section 10 sequentially outputsthe extracted voice characteristic pattern data to video retrieval indexgeneration section 11. Video retrieval index generation section 11collects items of the voice characteristic pattern data, inputsequentially, per unit time enabling synchronization between the videosignals and voice signals with the time series maintained, to make intopackets, and adds time information to each packet. Thereby the section11 generates an index structure that enables access to the video signalsor voice signals by referring to the time information using a positionof the voice characteristic pattern data, and outputs the generatedindex structure packets to complex data storage processing section 7sequentially.

Meanwhile video signal input section 5 also receives the instruction forstarting the video recording, performs A/D conversion on video signalsinput from an external device such as the television signal tuningdevice, camera, or VTR to quantize, and provides the video signals aspredetermined video signals to video signal encoding section 6 andvisual characteristic pattern extraction section 12. Video signalencoding section 6 performs video signal band compression processingsuch as the MPEG on the provided digital video signals to output tocomplex data storage processing section 7 sequentially.

Visual characteristic pattern extraction section 12 receives the videosignals from video signal input section 5, detects a portion of a humanlip area, and extracts a lip area image for each image frame of theinput video signals, using lip characteristic standard patterns fetchedfrom lip area images of some person internally registered in advance invisual characteristic pattern extraction section 12. To detect the liparea and extract the lip area image, used as an image characteristicpattern is color distribution histogram in color space in the lip area,and used as color distribution in image space is color information suchas color mean data and luminance mean data in each block obtained bydividing the lip area image into n.times.m image blocks (each of n and mis an arbitrary natural number, n is the number of division on X axis,and m is the number of division on Y axis). Further considering that asize of a lip area varies in an input image frame, a size of the liparea image is made variable to detect the lip area and extract the liparea image.

When visual characteristic pattern extraction section 12 detects andextracts the lip area from the input image frame, the section 12 furtherextracts the visual characteristic pattern data at the time of humanvocalizing from the extracted lip area image.

Used as the visual characteristic pattern is information representativeof a form of a lip. One example is vector data with componentscorresponding to the number of divided image blocks, where eachcomponent is comprised of color mean data or luminance mean data of eachimage block, used in extracting the lip area image, obtained by dividinga lip area image space into an arbitrary number of blocks. Anotherexample is vector data with 4 numerical components obtained by furtherextracting only a lip portion from the lip area image data extracted asthe visual characteristic, using, for example, a color filter, andcalculating a respective relative distance of two points eachcircumscribing a lip outer boundary in a vertical direction (upper andlower) and of two points each circumscribing the lip outer boundary in ahorizontal direction, each from an area centroid point of the lipportion.

Voice characteristic pattern extraction section 10 sequentially outputsthe extracted voice characteristic pattern data to video retrieval indexgeneration section 11, and visual characteristic pattern extractionsection 12 outputs the extracted visual characteristic pattern data tovideo retrieval index generation section 11. Video retrieval indexgeneration section 11 collects items of each of the voice characteristicpattern data and visual characteristic pattern data, each inputsequentially, per unit time enabling synchronization between the videovoice signals and voice signals with the time series maintained, to makeinto packets for each type of characteristic pattern data, and adds timeinformation and an identification indicative of the type ofcharacteristic pattern data to each packet. Thereby the section 11generates an index structure packet that enables access to the videosignals and voice signals by referring to the time information usingpositions of the voice characteristic pattern data and visualcharacteristic data, and outputs the generated index structure packet tocomplex data storage processing section 7 sequentially.

Complex data storage processing section 7 receives the instruction forstarting the video recording, issues the control signal to storagemedium operation control section 8 before starting recording data, andholds a data recording starting position in storage medium 9. Complexdata storage processing section 7 receives the video signals and voicesignals each applied the signal band compression processing, and theindex structure packets generated in video retrieval index generationsection 11, multiplexes the video signals, voice signals and indexstructure packet data in predetermined format such as the MPEG, issuesthe control signal to storage medium operation control section 8, andrecords the multiplexed data at a predetermined position on videostorage medium 9 according to the recording format such as the DVD.

The sequence of operations as described above is iterated during thetime from video recording is started to video recording control section2 detects elapse of video recording time, finish of video signal inputfrom the external, video recording halt instruction by the controlsignal from the external, or an error notification from a section insidethe apparatus. When video recording control section 2 detects either ofthe above-mentioned conditions, the section 2 instructs each sectioncomposing the apparatus to halt the video recording, shits the apparatusstate to the initial state, and thereby finishes the operation.

Thus the visual characteristic pattern data at the time of humanvocalizing is extracted from the video signals, and used along with thevoice characteristic pattern data to generate the video retrievalindexes. Therefore it is possible to supplement voice recognitionaccuracy when the recognition accuracy is decreased due to BGM(Background Music) and environment noise.

Sixth Embodiment

A video reproduction apparatus according to the sixth embodimentperforms video retrieval with a key word and quick reproduction, usingvideo retrieval indexes stored in the method as described in the fourthembodiment or fifth embodiment.

FIG. 12 illustrates a configuration of the video reproduction apparatusaccording to the sixth embodiment. Control signal input section 1receives signals such as video reproduction instruction control signalinput from an external. Video reproduction control section 13 issues arecording start instruction signal and halt instruction signal to eachblock composing the apparatus corresponding to types of received controlsignals. Video storage medium 9 stores video signals and voice signalsincluding video retrieval indexes generated in the method as describedin the fourth or fifth embodiment in predetermined recording format suchas the DVD. As video storage medium 9, it may be possible to use, forexample, an optical disk, HDD (magnetic disk), memory card or magnetictape. Complex data read processing section 7 reads the video signal andvoice signal from a time position indicative of a video reproductionposition according to the recording format in video storage medium 9 byan instruction from video reproduction control section 13, and furtherreads the video retrieval index. At this point, storage medium operationcontrol section 8 performs physical control such as a seek to a positionwhere data to be read is recorded, by a control instruction from complexdata read processing section 7.

Voice signal decoding section 15 compresses a signal band of the voicesignals subjected to signal band decompression processing such as theMPEG provided from complex data read processing section 14. Voice signaloutput section 16 performs D/A conversion on the voice signals subjectedto the signal band compression processing to output to an external.Further video signal decoding section 17 compresses a signal band of thevideo signals subjected to signal band decompression processing such asthe MPEG provided from complex data read processing section 14. Videosignal output section 18 performs D/A conversion on the voice signalssubjected to the signal band compression processing to output to anexternal.

Video retrieval index formation section 21 forms a video retrieval indextable using the video retrieval index data provided from complex dataread processing section 14. Storage circuit 23 temporarily stores theformed index table.

Meanwhile key word input section 19 receives a key word input from anexternal. Key word pattern conversion section 20 converts the input keyword into a phoneme code sequence, and further converts the sequenceinto pattern data used in pattern collation. Key word pattern collationsection 22 performs pattern collation of the time series of thecharacteristic pattern data of the key word with the time series of thecharacteristic pattern data in the video retrieval index table read fromstorage circuit 23. The video reproduction apparatus as described aboveis comprised of, for example, a microcomputer incorporated device ordedicated LSI circuits.

The following explains the operation of this apparatus.

When control signal input section 1 receives a control signalinstructing video reproduction from an external input device such as aremote control device or keyboard, the section 1 converts the controlsignal into a signal of format adapted to the apparatus, and issues avideo recording instruction signal to video reproduction control section13. Video reproduction control signal 13 receives the video recordinginstruction signal, and instructs complex data read processing section14 to start video recording, for example, with time informationindicative of a head of video signals.

Complex data read processing section 14 receives the instruction forstarting the video reproduction, and using the instructed timeinformation, determines respective read positions of the video signalsand voice signals, each in advance subjected to the signal banddecompression processing such as the MPEG, stored in video storagemedium 9 in predetermined recording format such as the DVD. The section14 issues a control signal instructing, for example, seek to respectiveread positions of the video signals and voice signals, to storage mediumoperation control section 8, and reads the video signals and voicesignals from video storage medium 9 while maintaining timesynchronization.

The video signals read by complex data read processing section 14 areprovided to video signal decoding section 17. The section 17 performsthe signal band compression processing such as the MPEG on the providedsignals to provide to video signal output section 18. The section 18performs D/A conversion on the provided signals to convert into, forexample, NTSC analog signals, and outputs the signals to an externaldevice such as a television monitor.

Similarly the voice signals read by complex data read processing section14 are provided to voice signal decoding section 16. The section 16performs the signal band compression processing such as the MPEG on theprovided signals to provide to voice signal output section 16. Thesection 16 performs D/A conversion on the provided signals to convertinto analog voice signals, and outputs the signals to an external devicesuch as a speaker.

When control signal input section 1 receives the control signalinstructing video reproduction from an external input device such as aremote control device or keyboard, the section 1 converts the controlsignal into the signal of format adapted to the apparatus, and issues avideo retrieval instruction signal to video reproduction control section13.

Video reproduction control signal 13 receives the video retrievalinstruction, and issues a control signal instructing to input a key wordto key word input section 19.

When key word input section 19 receives the key word input from theexternal input device such as a keyboard, the section 19 notifies videoreproduction control section 13 that input of the key word is completed,and outputs the input key word information to key word patternconversion section 20.

Video reproduction control section 13 receives the notification thatinput of the key word is completed, and initializes a key word detectedposition management table provided inside video reproduction controlsection 13 to manage time information indicative of a key word detectedposition in video signals. Then the section 13 issues an instruction forreading the video retrieval index data to complex data read processingsection 14, and further issues another instruction for starting patterncollation to key word pattern collation section 22. At this point, whenused as video storage medium 9 is a storage medium that ensures highaccessibility such as a memory card, HDD or optical disk, normal videoreplay is continued, while when used as video storage medium 9 is astorage medium without the high accessibility such as a magnetic tape,the normal video replay is once halted.

Key word pattern conversion section 20 receives the key wordinformation, converts the key word into a phoneme code sequence, andfurther converts the phoneme code sequence of the key word into the timeseries of voice characteristic pattern data corresponding to subwordscomposing the key word, referring to the standard voice patterncomprised of the time series of characteristic pattern data of eachsubword registered in advance in the section 20, to output to key wordpattern collation section 22.

Herein the data used as the standard voice pattern and the time seriesof voice characteristic pattern data is, as well as the voicecharacteristic pattern data used in the above-mentioned fourth and fifthembodiments, the time series of vector data with N (N is an arbitrarynatural number) components comprised of acoustic characteristic amountsgenerally used in voice recognition processing, such as short-termspectral data or logarithmic value of spectra at a human voice frequencyband, and logarithmic energy of the voice signals per unit time.

Meanwhile complex data read processing section 14 receives theinstruction for reading the video retrieval index data, from videoreproduction control section 13, issues a control signal instructing,for example, seek to a read position of the video retrieval index dataand high-rate read to storage medium operation control section 8, readsthe video retrieval index data stored in video storage medium 9 in thepredetermined recording format at the high rate, and outputs the readvideo retrieval index data sequentially to video retrieval indexformation section 21.

The video retrieval index data is made of packets per predetermined unittime in the method as described in the fourth or fifth embodiments, andis the time series data comprised of voice characteristic pattern data,visual characteristic pattern data or phoneme similarity table obtainedby collating the time series data for each subword, with a type of indexdata and time information synchronous with the video signal and voicesignal added to each packet.

Video retrieval index formation section 21 reconstructs the videoretrieval index data output from complex data read processing section 14into the above-mentioned unit packet, and writes the reconstructed indexstructure packet in storage circuit 23 having FIFO (fast-in/fast-out)memory structure or circulating memory corresponding to a time lengthsufficient to collate key word, for each type of index data with thetime series maintained. Then whenever key word pattern collation section22 reads and discards the index structure packet from temporary storagecircuit 23, video retrieval index formation section 21 writes a newlyoutput and formed index structure packet in an available area in storagecircuit 23. In addition, when video retrieval index formation section 21detects a final portion of the index data, the section 21 notifies keyword pattern collation section 22 that the read of index is completed.

Meanwhile key word pattern collation section 22 receives the instructionfor starting the pattern collation from video reproduction controlsection 13, and initializes internal processing and storage circuit 23.Then the section 22 receives the time series of voice characteristicpattern data of the key word output from key word pattern conversionsection 20, and collates the time series of voice characteristic patterndata in the index structure packet arranged in the order of time instorage section 23 by video retrieval index formation section 21 with atime interval sufficient for the pattern collation maintained, with thetime series of voice characteristic pattern data of the received keyword.

In the pattern collation, key word pattern collation section 22 expandsor contracts a collation interval using, for example, the DP collationmethod, within a predetermined time interval in the time series of thevoice characteristic pattern data in the index structure packet arrangedin the order of time in storage section 23, and obtains a collationinterval, as a detected interval of the key word, that obtains apredetermined degree of similarity that is a sum of similarities ofrespective voice characteristic pattern data when the time series of thevoice characteristic pattern data is formed as the key word.

In collating the patterns, key word pattern collation section 22 usesthe time series pattern collation such as the DP collation method, anditerates the collation, while sequentially reading and discarding thecollated index structure packet in storage circuit 23 to update.Whenever the section 22 obtains the predetermined degree of similarityat a collation iterated step, the section 22 notifies video reproductioncontrol section 13 of the time information, as a key word data detectedposition, which is contained in the index structure packet with firstvoice characteristic pattern data in the time series of the voicecharacteristic pattern data. In addition, in the case where key wordpattern collation section 22 receives the notification that the read ofthe index is finished from video retrieval index formation section 21,the section 22 completes the collation processing of voicecharacteristic pattern data in the index structure packet left instorage circuit 23, and notifies video reproduction control section 13that the key word collation is finished.

When video reproduction control section 13 receives first timeinformation indicative of the key word detected position from key wordpattern collation section 22, the section 13 once stores the receivedtime information at a head of the key word detected position managementtable stored internally, and issues an instruction for reproducing videobased on the received time information to complex data read processingsection 14. Then the apparatus performs the same processing as thenormal video replay, and outputs the video signals and voice signalsfrom a position of the time information indicative of the key worddetected position to an external of the apparatus.

When video reproduction control section 13 receives second and more timeinformation indicative of the key word detected position, the section 13sequentially stores the received time information from a second positionfrom the head position in the key word detected position managementtable. Then only in the case where an instruction indicative ofreproducing a next candidate is input from the external to the section13 through control signal input section 1, the section 13 fetches thetime information sequentially from the key word detected positionmanagement table, issues the instruction for reproducing video from adesignated time position to complex data read processing section 14.Then the apparatus performs the same processing as the normal videoreplay, and outputs the video signals and voice signals from a positionof the time information indicative of the key word detected position toan external of the apparatus.

Video reproducing control section 13 maintains contents of the key worddetected position management table even after receiving the notificationindicative of finish of key word collation from key word patterncollation section 22. Therefore whenever receiving a next candidatereproduction instruction from the external after finishing the key wordpattern collation processing, the section 13 is capable of fetching thetime information sequentially from the key word detected time managementtable, and issuing the instruction for reproducing video from theinstructed time position to complex data read processing section 14. Thekey word detected position management table is initialized when a newkey word is input from an external for a next video retrievalinstruction from the external.

This apparatus iterates the above-mentioned sequence of operationswhenever receives a video retrieval instruction with a key word from anexternal, and thereby is capable of specifying a video scene by the keyword collation with voice information of a video program, and quicklyreproducing the video from a specified position.

In the above explanation, the index structure packet data is the timeseries of voice characteristic pattern data. Further it may be possibleto adopt a constitution where key word pattern collation section 22performs pattern collation using a subword sequence of an input key wordand the similarity per subword basis in the above-mentioned phonemesimilarity table. In this case, key word pattern conversion section 20converts a key word output from key word input section 19 into a phonemecode sequence of the key word to output to key word pattern collationsection 22.

When key word pattern collation section 22 receives an instruction forstarting pattern collation from video reproduction control section 13,the section 22 initializes internal processing and storage section 23.Then the section 22 receives the phoneme code sequence of the key wordoutput from key word pattern conversion section 20, and collates thetime series of phoneme similarity table data in the index structurepacket arranged in the order of time in storage section 23 by videoretrieval index formation section 21 with a time interval sufficient forthe pattern collation maintained, with the time series of phoneme codesequence of the received key word.

In the pattern collation, key word pattern collation section 22 expandsor contracts a collation interval using, for example, a time expansionand contraction used in the DP collation method, within a predeterminedtime interval in the time series of the phoneme similarity table data inthe index structure packet arranged in the order of time in storagesection 23, and obtains a collation interval, as a detected interval ofthe key word, that obtains a predetermined degree of similarity that isa sum of similarities of respective subwords when the time series of thephoneme sequence is formed as the key word.

That is, key word pattern collation section 22 fetches index structurepackets each with an interval length sufficient for pattern collationfrom the phoneme similarity table with the same time width as a recordedvideo, and arranges voice characteristic pattern data items (withbeginning time, ending time and similarity) of the fetched indexstructure packets in the order of time. Voice characteristic patterndata corresponding to the number of all standard voice patterns(subwords) are arranged on the same time axis at an interval in thephoneme similarity table. The columns of the voice characteristicpattern data are arranged successively corresponding to the number ofintervals with an interval length sufficient for the pattern collation.Key word pattern collation section 22 collates time series of the voicecharacteristic pattern data of thus obtained video retrieval index withthe time series of the voice characteristic pattern data composing thekey word, while expanding or contracting a collation interval using theDP collation method, and sets a collation interval with a similaritybetween both time series higher than a predetermined level to be adetected interval of the key word. The similarity between both timeseries is obtained by fetching voice characteristic pattern data of theindex structure packet in the order of subword sequence composing thekey word, and adding similarities of the fetched voice characteristicpattern data.

The beginning time of the head subword in the key word detected intervalis notified to video reproduction control section 13 as the key worddetected position every time.

According to the pattern collation method as described above, since itis not necessary to perform collation processing between vector datacomprised of acoustic property components such as the time series ofvoice characteristic pattern data in pattern collation processing, it ispossible to largely reduce a collation processing time.

Further since the video retrieval index is not held in a fixed formcorresponding to a registered key word, but stored in an intermediateform of a phoneme similarity table of an input voice, it is notnecessary to register retrieval key words in advance, and to retrieve avideo accurately reflecting a retrieval purpose even in the case where auser inputs an uncertain key word.

Furthermore it may be possible to adopt a constitution where the keyword pattern conversion section converts an input key word into visualcharacteristic pattern data, and the above-mentioned key word patterncollation section uses the visual characteristic pattern data at thetime of human vocalizing as described in the fifth embodiment, as thevideo retrieval index stored in advance in a storage medium, andcollates the above-mentioned visual data with visual characteristicpattern data of an input key word, as follows:

In this case, key word pattern conversion section 20 converts key wordinformation output from key word input section 19 into a phoneme codesequence, and further converts the phoneme code sequence of the key wordinto time series of voice characteristic pattern data and time series ofvisual characteristic pattern data each corresponding to subwordscomposing the key word, referring to phoneme standard patterns comprisedof the time series of voice characteristic pattern data of respectivesubwords and visual characteristic standard patterns comprised of visualcharacteristic pattern data of respective vocalized subwords eachregistered in advance in the section 20, to output to key word patterncollation section 22.

Key word pattern collation section 22 receives the instruction forstarting the pattern collation from video reproduction control section13, and initializes internal processing and storage circuit 23. Then thesection 22 receives the time series of voice characteristic pattern dataand the time series of visual characteristic pattern data of the keyword output from key word pattern conversion section 20, and performsthe pattern collation using time series data in respective indexstructure packets in storage circuit 23 for each data type. Storagecircuit 23 stores the index structure packets comprised of the voicecharacteristic pattern data, and the index structure packets comprisedof the visual characteristic pattern data, each arranged in the order oftime by video retrieval index formation section 21.

In each pattern collation, key word pattern collation section 22 expandsor contracts a collation interval using, for example, the DP collationmethod, within a predetermined time interval in the time series of therespective characteristic pattern data in the index structure packetsarranged in the order of time in storage section 23 to perform thepattern collation of the time series of respective characteristicpattern data of the key word, and obtains a sum of similarities betweenthe characteristic pattern data of respective subwords for each datatype to set to at a respective key word similarity.

Key word pattern collation section 22 sets as a detected interval of thekey word a collation interval that obtains a predetermined degree ofsimilarity that is a sum of the thus obtained key word similarity incollating the time series of voice characteristic pattern data and keyword similarity in collating the time series of visual characteristicpattern data. Then the section 22 every time notifies video reproductioncontrol section 13 of the time information, as a key word data detectedposition, which is contained in the index structure packet with firstvoice characteristic pattern data in the time series of the voicecharacteristic pattern data in the detected interval.

Thus the pattern collation is performed using both the voicecharacteristic pattern data from a voice, and the visual characteristicpattern data from a video. Therefor, for example, even in the case ofdecreased accuracy of acoustic property data composing the voicecharacteristic pattern data in the index structure packet due to BGM(Background Music) or noise in a recorded video program, it is possibleto prevent key word detection accuracy from decreasing largely by usingthe visual characteristic pattern data.

Further it may be possible to adopt a constitution where the key wordinput section is provided with a microphone for use in inputting avoice, and the key word pattern conversion section converts a voicesignal of an input key word into the voice characteristic pattern dataof the key word, as follows:

When key word input section 19 receives a key word input from anexternal voice input device such as a microphone, the section 19notifies video reproduction control section 13 that input of the keyword is completed, and performs A/D conversion on the input key wordvoice signal to provide to key word pattern conversion section 20.

Key word pattern conversion section 20 performs FFT (Fast FourierTransform) on the input key word voice signal per unit time, extractsthe acoustic property data at a human voice frequency band, andgenerates the time series of voice characteristic pattern data comprisedof vector data with N (N is an arbitrary natural number) componentscomprised of acoustic characteristic amounts generally used in voicerecognition processing, such as short-term spectral data or logarithmicvalue of spectra at the extracted frequency band, and logarithmic energyof the voice signals per unit time.

It is thus possible to input a key word with a voice using, for example,a microphone, and generate the time series of voice characteristicpattern data required for the key word collation from the input voicesignal.

Further it may be possible to adopt a constitution where the key wordinput section is provided with a microphone and camera device for use ininputting a moving video, and the above-mentioned key word patternconversion section collates a video signal input when a user vocalizes akey word with lip image characteristic patterns registered in advancefor each vocalized sound, and converts the video signal when the uservocalizes the key word into the visual characteristic pattern data ofthe key word, as follows:

In this case, when key word input section 19 receives key wordinformation input from an external voice input device such as amicrophone and video camera device, the section 19 notifies videoreproduction control section 13 that input of the key word is completed,and processes A/D conversion on the input key word voice signal andvideo signal of a user's face when the user vocalizes the key word toprovide to key word pattern conversion section 20.

Key word conversion section 20 generates, from the input key word voicesignal, the time series of voice characteristic pattern data comprisedof vector data with N (N is an arbitrary natural number) componentscomprised of acoustic characteristic amounts generally used in voicerecognition processing. Further the section 20 detects a portion of ahuman lip area and extracts a lip area image for each image frame of theinput key word video signal, using lip characteristic standard patternsfetched from the lip area images of some person registered in advance,further extracts the visual characteristic pattern data at the time ofhuman vocalizing, which is comprised of information representative of aform of a lip, from the extracted lip area image, and generates the timeseries of visual characteristic pattern data corresponding to a key wordvocalized time. The section 20 outputs both time series data to key wordpattern collation section 22.

One example of the visual characteristic pattern data is vector datawith components corresponding to the number divided image blocks, whereeach component is comprised of color mean data or luminance mean data ofeach image block, used in extracting the lip area image, obtained bydividing a lip area image space into an arbitrary number blocks. Anotherexample is vector data with 4 numerical components obtained by furtherextracting only a lip portion from the lip area image data extracted asthe visual characteristic, using, for example, a color filter, andcalculating respective relative distances of two points eachcircumscribing a lip outer boundary in vertical direction (upper andlower) and of two points each circumscribing the lip outer boundary in ahorizontal direction, each from an area centroid point of the lipportion.

It is thus possible to input a key word with a video and voice using amicrophone and video camera device, and generate both the time series ofvoice characteristic pattern data of the key word from the input voicesignal, and the time series of video characteristic pattern data of thekey word from the input video signal.

Further the scene retrieval system of the present invention isapplicable to a scene retrieval for only voice. According to theabove-mentioned method, video signals, voice signals and video retrievalindexes, or voice signals and voice/video retrieval indexes are storedin a storage medium. It may be possible to use the voice/video retrievalindex with the same structure as that of the above-mentioned videoretrieval index. It may be possible to start retrieving a voice signalfrom a position corresponding to a beginning time of a head subword in akey word detected interval.

This application is based on the Japanese Patent ApplicationsNo.HEI10-359414 filed on Dec. 17, 1998, and HEI11-352819 filed on Dec.13, 1999, entire contents of which are expressly incorporated byreference herein.

Industrial Applicability

By using voice recognition techniques separately at the time of videorecording and at the time of video reproducing, it is possible toperform fast video retrieval using an arbitrary key word at the time ofvideo reproducing, and to achieve quick reproduction of a scene inaccordance with a user's purpose of retrieving.

Further since the video retrieval indexes are automatically generatedconcurrently with video recording, it is expected to largely reducelabors, which are manually performed conventionally, required forindexing operations with the purpose of arranging and reusing videos.Therefore the present invention has advantages in fields such as fromspecialized reproduction function using a digital video camera ordigital video tape recorder in homes to video signal base constructionand video retrieval/view in large-scale digital video library systems.

Brief Statement Under Article 19(1)

Claims 1, 12, 13 and 27 clarify that indexes are generated in advanceper subword basis, and in retrieving, a voice interval of a key word isobtained from a combination of indexes per subword basis correspondingto the key word.

Cited reference 1 (JP, 3-53379, A) relates to index generation withvoice recognition per word basis.

Cited reference 2 (Niimi, Yasunaga, Information Science Lecture E.19.3Voice Recognition, (JP), Kyoritsu Syuppan, (10.10.79) pages 90 to 93)relates to recognition using subword lattices in voice recognition.

Cited reference 3 (JP, 6-68168, A, paragraph numbers [0018] to [0019],drawing [FIG. 3]) relates to index generation with voice recognition perword basis, retrieval by referring to the indexes.

Cited reference 4 (JP, 5-108727, A) relates to performing retrieval byinputting and outputting a voice in inputting and outputting an image,and further performing remote control using a preexisting facsimile.

The present invention provides effects that it is possible to cope withany key word and perform fast retrieval in retrieving, by generatingindexes per subword basis, and further to transmit the indexes that doesnot require manual operation, by completely separating generation of theindexes and retrieval of the indexes.

We claim:
 1. A video retrieval apparatus comprising: a retrieval datagenerator that is configured to extract a characteristic pattern from avoice signal synchronous with a video signal to generate indexes forvideo retrieval; and a retrieval processor that is configured to input akey word from a retriever and collate the key word with the indexes toretrieve a desired video; wherein said retrieval data generator includesa multiplexor that is configured to multiplex video signals, voicesignals and indexes to output in data stream format; and wherein saidretrieval processor includes a demultiplexor that is configured todemultiplex the multiplexed data stream into the video signals, thevoice signals and the indexes.
 2. The video retrieval apparatusaccording to claim 1, wherein collating extracts the indexescorresponding to subwords contained in the input key word from a phonemesimilarity table comprised of indexes generated over an interval of thevoice signal to be retrieved, converts the extracted indexes into thetime series data to reconstruct the key word, and adds similarities foreach reconstructed key word.
 3. The video retrieval apparatus accordingto claim 1, wherein said retrieval data generator transmits the videosignal, the voice signal and the indexes to said retrieval processorthrough a transmission medium.
 4. The video retrieval apparatusaccording claim 3, wherein said transmission medium is either of abroadcast network, a communication network, or a storage medium.
 5. Thevideo retrieval apparatus according to claim 1, wherein said multiplexordivides the indexes into units that are brought into coincidence withunit GOP (Group of Videos) of corresponding video signals.
 6. The videoretrieval apparatus according to claim 5, wherein a time code of thevideo signal corresponding to the unit of the indexes is recorded astime synchronization information between the video signals, the voicesignals and the indexes.
 7. The video retrieval apparatus according toclaim 6, wherein the time code recorded in the unit of the indexesincludes a beginning time and a duration time of the video signalcorresponding to the unit.
 8. A video retrieval apparatus comprising: aretrieval data generator that is configured to extract a characteristicpattern from a voice signal synchronous with a video signal to generateindexes for video retrieval; and a retrieval processor that isconfigured to input a key word from a retriever and collate the key wordwith the indexes to retrieve a desired video, said retrieval processorincluding a receiver that is configured to receive the key word from aretrieval terminal connected through a communications network, and saidretrieval processor further including a transmitter that is configuredto transmit a retrieved video signal to the retrieval terminal throughthe communications network; wherein said retrieval data generatorincludes a multiplexor that is configured to multiplex video signals,voice signals and indexes to output in data stream format; and whereinsaid retrieval processor includes a demultiplexor that is configured todemultiplex the multiplexed data stream into the video signals, thevoice signals and the indexes.
 9. A voice retrieval apparatuscomprising: a retrieval data generator that is configured to extract acharacteristic pattern from a voice signal to generate indexes for voiceretrieval; and a retrieval processor that is configured to input a keyword from a retriever and collate the key word with the indexes toretrieve a desired voice; wherein said retrieval data generator includesa multiplexor that is configured to multiplex video signals, voicesignals and indexes to output in data stream format; and wherein saidretrieval processor includes a demultiplexor that is configured todemultiplex the multiplexed data stream into the video signals, thevoice signals and the indexes.
 10. A video reproduction apparatus thatperforms reproduction of video signals, said apparatus comprising: astorage medium that stores video signals and that stores video retrievalindexes generated based on an input voice; a key word pattern converterthat is configured to convert a key word input from a retriever intopattern collation data; and a key word pattern collator that isconfigured to collate the pattern collation data of the key word withpattern collation data in the video retrieval indexes of a video programstored in said storage medium; wherein said key word pattern converterconverts the input key word into visual characteristic pattern data; andwherein said key word pattern collator collates the visualcharacteristic pattern data of the input key word with visualcharacteristic pattern data of the video signals at the time a personvocalizes a sound as the video retrieval indexes stored in said storagemedium.
 11. The video reproduction apparatus according to claim 10,wherein said apparatus further comprises a microphone for use ininputting a voice, and said key word pattern converter converts a voicesignal of the key word input from said microphone into voicecharacteristic pattern data.
 12. The video reproduction apparatusaccording to claim 10, wherein said apparatus further comprises amicrophone and a camera apparatus for use in inputting a moving video,and said key word pattern converter collates a video signal input fromthe storage medium at the time a user vocalizes a key word with lipimage characteristic pattern pre-registered for each vocalized sound,and converts the video signal at the time the user vocalizes the keyword into visual characteristic pattern data of the key word.